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Agents.jl

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Agents.jl is a pure Julia general-purpose framework for agent-based modeling (ABM): a computational simulation methodology where autonomous agents react to their environment (including other agents) given a predefined set of rules. Some major highlights of Agents.jl that set it apart from other similar frameworks are:

  1. It is simple: has a very short learning curve and requires writing minimal code
  2. Has an extensive interface of thousands of out-of-the box possible agent actions
  3. It is fast (typically faster than established competitors)
  4. Straightforwardly allows simulations on Open Street Maps
  5. Allows both traditional discrete-time ABM simulations as well as continuous time "event queue" based ABM simulations
  6. Provides native integration of ABM simulations with Reinforcement Learning (RL)

More information and an extensive list of features can be found in the documentation, which you can either find online or build locally by running the docs/make.jl file.

Agents.jl is part of JuliaDynamics, an organization dedicated to creating high quality scientific software.

Citation

If you use this package in a publication, or simply want to refer to it, please cite the paper below:

@article{Agents.jl,
  doi = {10.1177/00375497211068820},
  url = {https://doi.org/10.1177/00375497211068820},
  year = {2022},
  month = jan,
  publisher = {{SAGE} Publications},
  pages = {003754972110688},
  author = {George Datseris and Ali R. Vahdati and Timothy C. DuBois},
  title = {Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity},
  journal = {{SIMULATION}},
  volume = {0},
  number = {0},
}
source
Star us on GitHub!

If you have found this package useful, please consider starring it on GitHub. This gives us an accurate lower bound of the (satisfied) user count.

Latest news: Agents.jl v7

This new version brings two powerful and experimental features:

  1. Allowing the agent container to be based on StructVectors, using a Struct-of-Arrays internal layout. This can increase simulation computational performance however it currently only supports single agent types. To use this, pass container = StructVector to StandardABM or EventQueueABM constructors, as well as use the helper construct SoAType{A} for dispatch purposes instead of your agent type A (read the docstring of SoAType).
  2. Native integration of ABMs with Reinforcement Learning is now provided by the new model type ReinforcementLearningABM. To learn how to use this functionality checkout the new tutorial on the Boltzmann Wealth Model with Reinforcement Learning.

There is also a minor breaking change: the internal code for plotting has been fully reworked. This does not affect typical users, as all plotting API remains identical, but it does affect users that were extending plotting for custom spaces. As a result of this change, hovering data inspection is currently disabled.

Highlights

Software quality

  • Free and open source.
  • Small learning curve due to intuitive design based on a modular space-agnostic functional modelling implementation.
  • User-created models typically have much smaller source code versus implementations in other open source ABM frameworks (proof), making them faster to prototype and modify.
  • Excellent computational performance, typically faster than established competitors.
  • High quality, extensive documentation featuring tutorials, example ABM implementations, an extra zoo of ABM examples, integration examples with other Julia packages, and developer's docs.

Agent based modelling specifically

  • Universal model structure where agents are identified by a unique id: AgentBasedModel.
  • Extendable API that provides out of the box thousands of possible agent actions.
  • Support for many types of space: arbitrary graphs, regular grids, continuous space
  • Support for simulations on Open Street Maps including support for utilizing the road's max speed limit, finding nearby agents/roads/destinations and pathfinding.
    • See this highlight for a simulation of the whole city of Chicago.
  • Modular design allows the creation of entirely new types of space configurations that can be integrated fully with the rest of Agents.jl API with only a few lines of code.
  • Multi-agent support, for interactions between disparate agent species.
  • Support for both discrete time and continuous time (event queue or jump processes) type of simulations.
  • Scheduler interface (with default schedulers), making it easy to activate agents in a specific order (e.g. by the value of some property).
  • Automatic data collection in a DataFrame at desired intervals.
  • Aggregating collected data during model evolution.
  • Distributed computing.
  • Batch running and batch data collection.
  • Extensive pathfinding capabilities in continuous or discrete spaces.
  • Reinforcement learning native integration.
  • Customizable visualization support for all kinds of models via the Makie ecosystem: publication-quality graphics and video output.
  • Interactive applications for any agent based models, which are created with only 5 lines of code and look like this:

Getting started

To install Agents.jl, launch Julia and then run this command:

using Pkg; Pkg.add("Agents")

To learn how to use Agents.jl, please visit the Tutorial before anything else.

Use the latest released version

After adding Agents.jl to your project, please check if the most up to date stable version has been installed. The versions of the installed packages in the project can be checked by running Pkg.status(). Only the latest version of Agents.jl provides all the features described in this documentation. It is generally advised against using earlier versions as they will likely only work partially and are not supported anymore.

Design philosophy of Agents.jl

Agents.jl was designed with the following philosophy in mind:

Simple to learn and use, yet extendable and highly performant, allowing for fast and scalable model creation and simulation.

There are multiple examples that highlight this core design principle, that one will quickly encounter when scanning through our API page. Here we just give two quick examples: first, there exists a universal function nearby_agents, which returns the agents nearby a given agent and within a given "radius". What is special for this function, which is allowed by Julia's Multiple Dispatch, is that nearby_agents will work for any space type the model has, reducing the learning curve of finding neighbors in ABMs made with Agents.jl. An even better example is perhaps our treatment of spaces. A user may create an entirely new kind of space (e.g. one representing a planet, or whatever else) by only extending 5 functions, as discussed in our Creating a new space type documentation. Indeed, the simplicity of Agents.jl is due to the intuitive space-agnostic modelling approach we have implemented: agent actions are specified using generically named functions (such as "move agent" or "find nearby agents") that do not depend on the actual space the agents exist in, nor on the properties of the agents themselves. Overall this leads to ultra fast model prototyping where even changing the space the agents live in is matter of only a couple of lines of code.

Many other agent-based modeling frameworks have been constructed to ease the process of building and analyzing ABMs (see e.g. here for an outdated review), spanning a varying degree of complexity. In the page ABM Framework Comparison we compare how our design philosophy puts us into comparison with other well accepted ABM software. Fascinatingly, even though the main focus of Agents.jl is simplicity, ease of use, and extendability, it runs faster than all software we compared it with.

Crash course on agent based modeling

An agent-based (or individual-based) model is a computational simulation of autonomous agents that react to their environment (including other agents) given a predefined set of rules [1]. ABMs have been adopted and studied in a variety of research disciplines. One reason for their popularity is that they enable a relaxation of many simplifying assumptions usually made by mathematical models. Relaxing such assumptions of a "perfect world" can change a model's behavior [2].

Agent-based models are increasingly recognized as a useful approach for studying complex systems [3,4,5,6]. Complex systems cannot be fully understood using traditional mathematical tools which aggregate the behavior of elements in a system. The behavior of a complex system depends on both the behavior of and interactions between its elements (agents). Small changes in the input to complex systems or the behavior of its agents can lead to large changes in outcome. That is to say, a complex system's behavior is nonlinear, and that it is not only the sum of the behavior of its elements. Use of ABMs have become feasible after the availability of computers and has been growing ever since, especially in modeling biological and economic systems, and has extended to social studies and archaeology.

An ABM consists of autonomous agents that behave given a set of rules. A classic example of an ABM is Schelling's segregation model, which we implement as an example here. This model uses a regular grid and defines agents at random positions on the grid. Agents can be from different social groups. Agents are happy/unhappy based on the fraction of their neighbors that belong to the same group as they are. If they are unhappy, they keep moving to new locations until they are happy. Schelling's model shows that even small preferences of agents to have neighbors belonging to the same group (e.g. preferring that at least 30% of neighbors to be in the same group) could lead to total segregation of neighborhoods. This is an example of emergent behavior from simple interactions of agents that can only be captured in an agent-based model.

Getting help

You're looking for support for Agents.jl? Look no further! Here are some things you can do to resolve your questions about Agents.jl:

  1. Read the online documentation! It is likely that the thing you want to know is already documented, so use the search bar and search away!
  2. Chat with us in the channel #dynamics-bridged in the Julia Slack!
  3. Post a question in the Julia discourse in the category “Modelling and simulations”, using agents as a tag!
  4. If you believe that you have encountered unexpected behavior or a bug in Agents.jl, then please do open an issue on our GitHub page providing a minimal working example!

Contributing

Any contribution to Agents.jl is welcome! For example you can:

  • Add new feature or improve an existing one (plenty to choose from the "Issues" page)
  • Improve the existing documentation
  • Add new example ABMs into our existing pool of examples
  • Report bugs and suggestions in the Issues page

Have a look at contributor's guide of the SciML organization for some good information on contributing to Julia packages!

Citation

If you use this package in work that leads to a publication, then please cite the paper below:

@article{Agents.jl,
  doi = {10.1177/00375497211068820},
  url = {https://doi.org/10.1177/00375497211068820},
  year = {2022},
  month = jan,
  publisher = {{SAGE} Publications},
  pages = {003754972110688},
  author = {George Datseris and Ali R. Vahdati and Timothy C. DuBois},
  title = {Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity},
  journal = {{SIMULATION}},
  volume = {0},
  number = {0},
}

Reproducibility

The documentation of Agents.jl was built using these direct dependencies,
Status `~/work/Agents.jl/Agents.jl/docs/Project.toml`
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Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated`
and using this machine and Julia version.
Julia Version 1.12.5
Commit 5fe89b8ddc1 (2026-02-09 16:05 UTC)
Build Info:
  Official https://julialang.org release
Platform Info:
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  CPU: 4 × AMD EPYC 7763 64-Core Processor
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Threads: 1 default, 1 interactive, 1 GC (on 4 virtual cores)
Environment:
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A more complete overview of all dependencies and their versions is also provided.
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  [46757867] NetworkLayout v0.4.10
⌃ [76b6901f] OSMMakie v0.1.2
  [510215fc] Observables v0.5.5
  [6fe1bfb0] OffsetArrays v1.17.0
  [0b1bfda6] OneHotArrays v0.2.10
  [925886fa] OnlineStatsBase v1.7.1
  [52e1d378] OpenEXR v0.3.3
  [4d8831e6] OpenSSL v1.6.1
⌅ [3bd65402] Optimisers v0.3.4
  [bac558e1] OrderedCollections v1.8.1
⌅ [bbf590c4] OrdinaryDiffEqCore v1.30.0
⌃ [b1df2697] OrdinaryDiffEqTsit5 v1.5.0
  [90014a1f] PDMats v0.11.37
  [f57f5aa1] PNGFiles v0.4.4
  [f3bd98c0] POMDPLinter v0.1.3
⌅ [7588e00f] POMDPTools v0.1.6
⌅ [a93abf59] POMDPs v0.9.6
  [19eb6ba3] Packing v0.5.1
  [5432bcbf] PaddedViews v0.5.12
  [d96e819e] Parameters v0.12.3
  [69de0a69] Parsers v2.8.3
  [eebad327] PkgVersion v0.3.3
  [ccf2f8ad] PlotThemes v3.3.0
  [995b91a9] PlotUtils v1.4.4
  [91a5bcdd] Plots v1.41.6
  [f517fe37] Polyester v0.7.19
  [1d0040c9] PolyesterWeave v0.2.2
  [647866c9] PolygonOps v0.1.2
  [3a141323] PolynomialRoots v1.0.0
⌃ [f27b6e38] Polynomials v4.0.21
  [2dfb63ee] PooledArrays v1.4.3
  [aea7be01] PrecompileTools v1.3.3
  [21216c6a] Preferences v1.5.2
  [8162dcfd] PrettyPrint v0.2.0
  [08abe8d2] PrettyTables v3.2.3
  [27ebfcd6] Primes v0.5.7
  [33c8b6b6] ProgressLogging v0.1.6
  [92933f4c] ProgressMeter v1.11.0
  [3349acd9] ProtoBuf v1.3.0
  [43287f4e] PtrArrays v1.4.0
  [4b34888f] QOI v1.0.2
  [1fd47b50] QuadGK v2.11.2
  [94ee1d12] Quaternions v0.7.7
⌅ [30b38841] QuickHeaps v0.1.2
  [74087812] Random123 v1.7.1
  [e6cf234a] RandomNumbers v1.6.0
  [b3c3ace0] RangeArrays v0.3.2
  [c84ed2f1] Ratios v0.4.5
  [c1ae055f] RealDot v0.1.0
  [3cdcf5f2] RecipesBase v1.3.4
  [01d81517] RecipesPipeline v0.6.12
⌃ [731186ca] RecursiveArrayTools v3.36.0
  [189a3867] Reexport v1.2.2
  [dee08c22] RegionTrees v0.3.2
  [2792f1a3] RegistryInstances v0.1.0
  [05181044] RelocatableFolders v1.0.1
  [ae029012] Requires v1.3.1
  [79098fc4] Rmath v0.9.0
  [6038ab10] Rotations v1.7.1
  [5eaf0fd0] RoundingEmulator v0.2.1
  [7e49a35a] RuntimeGeneratedFunctions v0.5.17
  [fdea26ae] SIMD v3.7.2
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  [476501e8] SLEEFPirates v0.6.43
  [322a6be2] Sass v0.2.0
⌃ [0bca4576] SciMLBase v2.101.0
  [c0aeaf25] SciMLOperators v1.15.1
  [431bcebd] SciMLPublic v1.0.1
  [53ae85a6] SciMLStructures v1.10.0
  [7e506255] ScopedValues v1.5.0
  [6c6a2e73] Scratch v1.3.0
  [91c51154] SentinelArrays v1.4.9
  [efcf1570] Setfield v1.1.2
  [65257c39] ShaderAbstractions v0.5.0
  [605ecd9f] ShowCases v0.1.0
  [992d4aef] Showoff v1.0.3
  [73760f76] SignedDistanceFields v0.4.1
  [777ac1f9] SimpleBufferStream v1.2.0
  [699a6c99] SimpleTraits v0.9.5
  [ce78b400] SimpleUnPack v1.1.0
  [47aef6b3] SimpleWeightedGraphs v1.5.1
  [45858cf5] Sixel v0.1.5
  [a2af1166] SortingAlgorithms v1.2.2
  [dc90abb0] SparseInverseSubset v0.1.2
  [d4ead438] SpatialIndexing v0.1.6
  [276daf66] SpecialFunctions v2.7.1
  [171d559e] SplittablesBase v0.1.15
  [860ef19b] StableRNGs v1.0.4
  [cae243ae] StackViews v0.1.2
  [aedffcd0] Static v1.3.1
  [0d7ed370] StaticArrayInterface v1.9.0
  [90137ffa] StaticArrays v1.9.17
  [1e83bf80] StaticArraysCore v1.4.4
⌅ [4c8beaf5] StaticGraphs v0.3.1
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.8.0
  [2913bbd2] StatsBase v0.34.10
  [4c63d2b9] StatsFuns v1.5.2
  [ff63dad9] StreamSampling v0.7.6
  [7792a7ef] StrideArraysCore v0.5.8
  [892a3eda] StringManipulation v0.4.4
  [09ab397b] StructArrays v0.7.2
  [2efcf032] SymbolicIndexingInterface v0.3.46
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.12.1
  [899adc3e] TensorBoardLogger v0.1.26
  [62fd8b95] TensorCore v0.1.1
  [1c621080] TestItems v1.0.0
  [8290d209] ThreadingUtilities v0.5.5
  [731e570b] TiffImages v0.11.6
  [06e1c1a7] TiledIteration v0.5.0
  [e689c965] Tracy v0.1.6
  [3bb67fe8] TranscodingStreams v0.11.3
  [28d57a85] Transducers v0.4.85
  [410a4b4d] Tricks v0.1.13
  [981d1d27] TriplotBase v0.1.0
  [781d530d] TruncatedStacktraces v1.4.0
  [5c2747f8] URIs v1.6.1
  [3a884ed6] UnPack v1.0.2
  [1cfade01] UnicodeFun v0.4.1
  [b8865327] UnicodePlots v3.8.1
  [1986cc42] Unitful v1.28.0
  [013be700] UnsafeAtomics v0.3.0
  [41fe7b60] Unzip v0.2.0
  [98cad3c8] ValueHistories v0.5.6
  [3d5dd08c] VectorizationBase v0.21.72
  [ea10d353] WeakRefStrings v1.4.2
  [e3aaa7dc] WebP v0.1.3
  [efce3f68] WoodburyMatrices v1.1.0
  [76eceee3] WorkerUtilities v1.6.1
⌅ [e88e6eb3] Zygote v0.6.77
  [700de1a5] ZygoteRules v0.2.7
  [02a925ec] cuDNN v1.4.6
  [6e34b625] Bzip2_jll v1.0.9+0
  [4e9b3aee] CRlibm_jll v1.0.1+0
⌅ [d1e2174e] CUDA_Compiler_jll v0.3.1+1
  [4ee394cb] CUDA_Driver_jll v13.1.0+2
⌅ [76a88914] CUDA_Runtime_jll v0.19.2+0
  [62b44479] CUDNN_jll v9.17.1+0
  [83423d85] Cairo_jll v1.18.5+1
  [ee1fde0b] Dbus_jll v1.16.2+0
  [5ae413db] EarCut_jll v2.2.4+0
  [2702e6a9] EpollShim_jll v0.0.20230411+1
  [2e619515] Expat_jll v2.7.3+0
⌅ [b22a6f82] FFMPEG_jll v6.1.3+0
  [f5851436] FFTW_jll v3.3.11+0
  [a3f928ae] Fontconfig_jll v2.17.1+0
  [d7e528f0] FreeType2_jll v2.13.4+0
  [559328eb] FriBidi_jll v1.0.17+0
  [0656b61e] GLFW_jll v3.4.1+0
  [d2c73de3] GR_jll v0.73.22+0
  [b0724c58] GettextRuntime_jll v0.22.4+0
  [61579ee1] Ghostscript_jll v9.55.1+0
  [59f7168a] Giflib_jll v5.2.3+0
  [020c3dae] Git_LFS_jll v3.7.0+0
  [f8c6e375] Git_jll v2.53.0+0
  [7746bdde] Glib_jll v2.86.3+0
  [3b182d85] Graphite2_jll v1.3.15+0
  [528830af] Gumbo_jll v0.10.2+0
  [2e76f6c2] HarfBuzz_jll v8.5.1+0
  [c73af94c] ImageMagick_jll v7.1.2011+0
  [905a6f67] Imath_jll v3.2.2+0
  [1d5cc7b8] IntelOpenMP_jll v2025.2.0+0
  [aacddb02] JpegTurbo_jll v3.1.4+0
  [9c1d0b0a] JuliaNVTXCallbacks_jll v0.2.1+0
  [c1c5ebd0] LAME_jll v3.100.3+0
  [88015f11] LERC_jll v4.0.1+0
  [dad2f222] LLVMExtra_jll v0.0.38+0
  [1d63c593] LLVMOpenMP_jll v18.1.8+0
  [dd4b983a] LZO_jll v2.10.3+0
  [ad6e5548] LibTracyClient_jll v0.13.1+0
⌅ [e9f186c6] Libffi_jll v3.4.7+0
  [7e76a0d4] Libglvnd_jll v1.7.1+1
  [94ce4f54] Libiconv_jll v1.18.0+0
  [4b2f31a3] Libmount_jll v2.41.3+0
  [89763e89] Libtiff_jll v4.7.2+0
  [38a345b3] Libuuid_jll v2.41.3+0
  [d3a379c0] LittleCMS_jll v2.17.0+0
  [856f044c] MKL_jll v2025.2.0+0
  [c8ffd9c3] MbedTLS_jll v2.28.1010+0
  [e98f9f5b] NVTX_jll v3.2.2+0
  [e7412a2a] Ogg_jll v1.3.6+0
  [6cdc7f73] OpenBLASConsistentFPCSR_jll v0.3.30+0
  [18a262bb] OpenEXR_jll v3.4.4+0
  [643b3616] OpenJpeg_jll v2.5.5+0
  [9bd350c2] OpenSSH_jll v10.2.1+0
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [91d4177d] Opus_jll v1.6.1+0
  [36c8627f] Pango_jll v1.57.0+0
⌅ [30392449] Pixman_jll v0.44.2+0
⌅ [c0090381] Qt6Base_jll v6.8.2+2
⌅ [629bc702] Qt6Declarative_jll v6.8.2+1
⌅ [ce943373] Qt6ShaderTools_jll v6.8.2+1
⌃ [e99dba38] Qt6Wayland_jll v6.8.2+2
  [f50d1b31] Rmath_jll v0.5.1+0
  [a44049a8] Vulkan_Loader_jll v1.3.243+0
  [a2964d1f] Wayland_jll v1.24.0+0
  [02c8fc9c] XML2_jll v2.15.1+0
  [ffd25f8a] XZ_jll v5.8.2+0
  [f67eecfb] Xorg_libICE_jll v1.1.2+0
  [c834827a] Xorg_libSM_jll v1.2.6+0
  [4f6342f7] Xorg_libX11_jll v1.8.13+0
  [0c0b7dd1] Xorg_libXau_jll v1.0.13+0
  [935fb764] Xorg_libXcursor_jll v1.2.4+0
  [a3789734] Xorg_libXdmcp_jll v1.1.6+0
  [1082639a] Xorg_libXext_jll v1.3.8+0
  [d091e8ba] Xorg_libXfixes_jll v6.0.2+0
  [a51aa0fd] Xorg_libXi_jll v1.8.3+0
  [d1454406] Xorg_libXinerama_jll v1.1.7+0
  [ec84b674] Xorg_libXrandr_jll v1.5.6+0
  [ea2f1a96] Xorg_libXrender_jll v0.9.12+0
  [c7cfdc94] Xorg_libxcb_jll v1.17.1+0
  [cc61e674] Xorg_libxkbfile_jll v1.2.0+0
  [e920d4aa] Xorg_xcb_util_cursor_jll v0.1.6+0
  [12413925] Xorg_xcb_util_image_jll v0.4.1+0
  [2def613f] Xorg_xcb_util_jll v0.4.1+0
  [975044d2] Xorg_xcb_util_keysyms_jll v0.4.1+0
  [0d47668e] Xorg_xcb_util_renderutil_jll v0.3.10+0
  [c22f9ab0] Xorg_xcb_util_wm_jll v0.4.2+0
  [35661453] Xorg_xkbcomp_jll v1.4.7+0
  [33bec58e] Xorg_xkeyboard_config_jll v2.44.0+0
  [c5fb5394] Xorg_xtrans_jll v1.6.0+0
  [3161d3a3] Zstd_jll v1.5.7+1
  [1e29f10c] demumble_jll v1.3.0+0
  [35ca27e7] eudev_jll v3.2.14+0
  [214eeab7] fzf_jll v0.61.1+0
  [9a68df92] isoband_jll v0.2.3+0
  [a4ae2306] libaom_jll v3.13.1+0
  [0ac62f75] libass_jll v0.17.4+0
  [1183f4f0] libdecor_jll v0.2.2+0
  [2db6ffa8] libevdev_jll v1.13.4+0
  [f638f0a6] libfdk_aac_jll v2.0.4+0
  [36db933b] libinput_jll v1.28.1+0
  [b53b4c65] libpng_jll v1.6.55+0
  [47bcb7c8] libsass_jll v3.6.6+0
  [075b6546] libsixel_jll v1.10.5+0
  [f27f6e37] libvorbis_jll v1.3.8+0
  [c5f90fcd] libwebp_jll v1.6.0+0
  [337d8026] libzip_jll v1.11.3+0
  [009596ad] mtdev_jll v1.1.7+0
  [1317d2d5] oneTBB_jll v2022.0.0+1
⌅ [1270edf5] x264_jll v10164.0.1+0
  [dfaa095f] x265_jll v4.1.0+0
  [d8fb68d0] xkbcommon_jll v1.13.0+0
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [8bf52ea8] CRC32c v1.11.0
  [ade2ca70] Dates v1.11.0
  [8ba89e20] Distributed v1.11.0
  [f43a241f] Downloads v1.7.0
  [7b1f6079] FileWatching v1.11.0
  [9fa8497b] Future v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [ac6e5ff7] JuliaSyntaxHighlighting v1.12.0
  [4af54fe1] LazyArtifacts v1.11.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.12.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [a63ad114] Mmap v1.11.0
  [ca575930] NetworkOptions v1.3.0
  [44cfe95a] Pkg v1.12.1
  [de0858da] Printf v1.11.0
  [9abbd945] Profile v1.11.0
  [3fa0cd96] REPL v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [1a1011a3] SharedArrays v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.12.0
  [f489334b] StyledStrings v1.11.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.3.0+1
  [deac9b47] LibCURL_jll v8.15.0+0
  [e37daf67] LibGit2_jll v1.9.0+0
  [29816b5a] LibSSH2_jll v1.11.3+1
  [14a3606d] MozillaCACerts_jll v2025.11.4
  [4536629a] OpenBLAS_jll v0.3.29+0
  [05823500] OpenLibm_jll v0.8.7+0
  [458c3c95] OpenSSL_jll v3.5.4+0
  [efcefdf7] PCRE2_jll v10.44.0+1
  [bea87d4a] SuiteSparse_jll v7.8.3+2
  [83775a58] Zlib_jll v1.3.1+2
  [8e850b90] libblastrampoline_jll v5.15.0+0
  [8e850ede] nghttp2_jll v1.64.0+1
  [3f19e933] p7zip_jll v17.7.0+0
Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`

You can also download the manifest file and the project file.